Application of artificial intelligence in geotechnical engineering: A state-of-the-art review
Geotechnical engineering deals with soils and rocks and their use in engineering
constructions. By their nature, soils and rocks exhibit complex behaviours and a high level of …
constructions. By their nature, soils and rocks exhibit complex behaviours and a high level of …
BIM, machine learning and computer vision techniques in underground construction: Current status and future perspectives
The architecture, engineering and construction (AEC) industry is experiencing a
technological revolution driven by booming digitisation and automation. Advances in …
technological revolution driven by booming digitisation and automation. Advances in …
Optimization of support vector machine through the use of metaheuristic algorithms in forecasting TBM advance rate
The advance rate (AR) of a tunnel boring machine (TBM) in hard rock condition is a key
parameter for the successful accomplishment of a tunneling project, and the proper and …
parameter for the successful accomplishment of a tunneling project, and the proper and …
From knowledge-based to big data analytic model: a novel IoT and machine learning based decision support system for predictive maintenance in Industry 4.0
Abstract The Internet of Things (IoT), Big Data and Machine Learning (ML) may represent
the foundations for implementing the concept of intelligent production, smart products …
the foundations for implementing the concept of intelligent production, smart products …
[HTML][HTML] Predicting TBM penetration rate in hard rock condition: A comparative study among six XGB-based metaheuristic techniques
A reliable and accurate prediction of the tunnel boring machine (TBM) performance can
assist in minimizing the relevant risks of high capital costs and in scheduling tunneling …
assist in minimizing the relevant risks of high capital costs and in scheduling tunneling …
Metaheuristic-based support vector regression for landslide displacement prediction: A comparative study
Recently, integrated machine learning (ML) metaheuristic algorithms, such as the artificial
bee colony (ABC) algorithm, genetic algorithm (GA), gray wolf optimization (GWO) algorithm …
bee colony (ABC) algorithm, genetic algorithm (GA), gray wolf optimization (GWO) algorithm …
[HTML][HTML] Comparison of machine learning methods for ground settlement prediction with different tunneling datasets
L Tang, SH Na - Journal of Rock Mechanics and Geotechnical …, 2021 - Elsevier
This study integrates different machine learning (ML) methods and 5-fold cross-validation
(CV) method to estimate the ground maximal surface settlement (MSS) induced by …
(CV) method to estimate the ground maximal surface settlement (MSS) induced by …
Deep learning-based prediction of steady surface settlement due to shield tunnelling
Predicting ground movement produced by shield tunnelling in densely built urban areas is of
practical significance. This study introduces an artificial intelligence method to predict the …
practical significance. This study introduces an artificial intelligence method to predict the …
[HTML][HTML] Investigation of feature contribution to shield tunneling-induced settlement using Shapley additive explanations method
Accurate prediction of shield tunneling-induced settlement is a complex problem that
requires consideration of many influential parameters. Recent studies reveal that machine …
requires consideration of many influential parameters. Recent studies reveal that machine …
A hybrid metaheuristic approach using random forest and particle swarm optimization to study and evaluate backbreak in open-pit blasting
Backbreak is a rock fracture problem that exceeds the limits of the last row of holes in an
explosion operation. Excessive backbreak increases operational costs and also poses a …
explosion operation. Excessive backbreak increases operational costs and also poses a …